Results 21 to 30 of about 430,573 (198)
Quantum Regularized Least Squares [PDF]
Quantum, 2023 Linear regression is a widely used technique to fit linear models and finds widespread applications across different areas such as machine learning and statistics.
Shantanav Chakraborty +2 more
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A moving least squares meshless method for solving the generalized Kuramoto-Sivashinsky equation
Alexandria Engineering Journal, 2016 We use a moving least squares meshless method to solve the nonlinear Kuramoto-Sivashinsky equation. The accuracy of the method is demonstrated by three test problems for which the numerical results are found to be in excellent agreement with analytical ...
E. Dabboura, H. Sadat, C. Prax
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Open Journal of Mathematical Optimization, 2021 The M-P (Moore–Penrose) pseudoinverse has as a key application the computation of least-squares solutions of inconsistent systems of linear equations. Irrespective of whether a given input matrix is sparse, its M-P pseudoinverse can be dense, potentially
Fampa, Marcia, Lee, Jon, Ponte, Gabriel
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Some Insight into the Generalized Linear Least Squares Parameter Adjustment Methodology
EPJ Web of Conferences, 2016 Some features of the generalized linear least squares parameter adjustment procedure have been discussed and proved. In particular: the equivalence of the adjusted measured response values and their recalculated values with the adjusted parameters, the ...
Wagschal J.J.
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Panel Data Estimation for Correlated Random Coefficients Models
Econometrics, 2019 This paper considers methods of estimating a static correlated random coefficient model with panel data. We mainly focus on comparing two approaches of estimating unconditional mean of the coefficients for the correlated random coefficients models, the ...
Cheng Hsiao +3 more
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Semiparametric sieve-type generalized least squares inference [PDF]
, 2014 This article considers the problem of statistical inference in linear regression models with dependent errors. A sieve-type generalized least squares (GLS) procedure is proposed based on an autoregressive approximation to the generating mechanism of the ...
Anderson T. W. +7 more
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Analysis of MIMO Receiver Using Generalized Least Squares Method in Colored Environments
Journal of Computer Networks and Communications, 2014 The classical detection techniques for multiple-input multiple-output (MIMO) systems are usually designed with the assumption that the additive complex Gaussian noise is uncorrelated. However, for closely spaced antennas, the additive noise is correlated
Mohamed Lassaad Ammari, Paul Fortier
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Comparison among autocorrelation factor value ( ) in estimation of generalized least squares method [PDF]
المجلة العراقية للعلوم الاحصائية, 2006 This research concerns to find appropriate method among all the methods of estimation the Autocorrelation factor value , to get rid of Autocorrelation problem , among the random variable to gain the most accurate value which is studied in generalized ...
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Estimating multilevel models for categorical data via generalized least squares
Revista Colombiana de Estadística, 2005 Montero et al. (2002) proposed a strategy to formulate multilevel models related to a contingency table sample. This methodology is based on the application of the general linear model to hierarchical categorical data. In this paper we applied the method
MINERVA MONTERO DÍAZ, VALIA GUERRA ONES
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Generalized Least Squares Estimation [PDF]
, 2018 When the errors in a regression model are independent and identically distributed, the Gauss-Markov theorem establishes that the ordinary least squares (OLS) estimator is “BLUE” (Best Linear Unbiased Estimator) (see Chap. 2). So far, all of the examples we have encountered in this text have met these assumptions, but in this chapter you will learn how ...
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